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Determination of Surface Runoff in Amreli District Gujarat, India Using GIS Based SCS Curve Number Method (IJSTE/ Volume 2 / Issue 11 / 066)

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Determination of Surface Runoff in Amreli District Gujarat, India Using GIS Based SCS Curve Number Method (IJSTE/ Volume 2 / Issue 11 / 066) IJSTE - International Journal of Science Technology & Engineering | Volume 2 | Issue 11 | May 2016 ISSN (online): 2349-784X Determination of Surface Runoff in Amreli District Gujarat, India using GIS based SCS Curve Number Method Nidhi B Chauhan Prof. M. S. Gadhavi M.E. Student Assistant professor L.D College of Engineering, Ahmedabad L.D College of Engineering, Ahmedabad Dr. Indra Prakash Khalid Mehmood BISAG, Gandhinagar BISAG, Gandhinagar Abstract Among the most basic challenges of hydrology are the prediction and quantification of runoff of the area. The runoff curve number (CN) is a key factor in determining runoff is the SCS (Soil Conservation Service) based hydrologic modeling method. In this paper soil conservation system (SCS) curve number method is used for rainfall-runoff estimation that consider parameters like slope, vegetation cover, area of watershed. SCS-CN provides empirical relationship for estimating surface runoff as a function of soil type and land use. Surface runoff is calculated for the Amreli district in Gujarat, India where heavy Rainfall occurred in June 2015 using the GIS-based SCS-CN method. The estimated composite curve number for the entire Amreli District is about 87. The present study clearly demonstrates that that the integration of GIS with the SCS-CN method provides a powerful tool for estimating surface runoff in Amreli District. Keywords: Surface Runoff, GIS, Amreli, SCS-CN ________________________________________________________________________________________________________ I. INTRODUCTION Runoff is the drainage of precipitation from a catchment, which flows out through its natural drainage system. After the occurrence of infiltration and other losses from the precipitation, the excess rainfall flows out through the small natural channels on the land surface to the main drainage channel. Most environmental process show complicated interrelations, both time and space, leading to numerical models with a complex mathematical structure. Also environmental models require huge amount of data often coming from many sources like Remote Sensing. Knowledge of runoff that depends upon many factors like precipitation, recharge of the basin, type of soil etc. is one of such important parameter. Most of the watersheds in dry land areas are un-gauged and very limited hydrological data are available. For most efficient utilization of available rainwater, reasonable accurate estimate of runoff for a given storm for a watershed is essential. Further from a rain fed watershed, along with the assessment of above runoff, the assessment of soil moisture throughout the crop growth period is vital due to erratic distribution of rainfall Many investigators has developed and applied models based on various levels of physical simplifications. However, there are some important models that fetches enormous application to Indian conditions like rational method, khosla’s model, cook’s model and SCS Rainfall-Runoff model. As against all the above models, SCS Rainfall –Runoff Model is well-established model reflecting quite an exhaustive research database all over the world. In India considerable research has been done in different soil climatic regions and succeeded in arriving at various co-efficient used in this method. Most of the parameters that are affecting runoff are taken into account in this model. Each parameter in turn, is classified precisely into a number of classes depending on their runoff producing potential. This method also takes into account the distribution of rainfall with time in the form of AMC conditions. Some of the parameters are amenable from remote sensing data. Since most of the input data is geographic in nature, performance of analyses becomes easier with the use of GIS. Hence, SCS Rainfall-Runoff model has been chosen to study the hydrologic response of a watershed to precipitation and estimate runoff volumes for adopting various water conservation measures. II. STUDY AREA District Amreli is located near the Gulf of Khambhat in western India. Its mainland extends between 20 degree - 45 min and 22 degree – 00 min north latitude and between 70 degree 50 Min and 71 degree - 40-min longitude. District is bound by district Bhavnagar in the East, Junagadh in the West, Rajkot in the North and Arabian Sea in the south. It covers 7381 sq.km Area. It has population of 15, 14,190 as per 2011 census. District has 11 talukas which are Amreli, Babra, Bagasara, Dhari, Jafrabad, Khamba, Lathi, Liliya, Rajula, Savarkundla and Vadiya. Amreli has 9 Urban Local Bodies (ULB), namely Amreli, Bagasara, Chalala, All rights reserved by www.ijste.org 367 Determination of Surface Runoff in Amreli District Gujarat, India using GIS based SCS Curve Number Method (IJSTE/ Volume 2 / Issue 11 / 066) Damnagar, Jafrabad, Lathi, Rajula, Savarkundla and Babra. District has total 626 revenue villages and population density of 205 inhabitants per square km. Climate of Amreli district can be regarded as one of the extreme kind with hot summer and cold winter except in the coastal region, where it is generally pleasant throughout the year. The air is humid in costal locations. The temperature at district headquarters ranges from 45 degree centigrade higher in the summer and 4.2 degree centigrade lowest in the winter. The average annual rainfall is 609 mm. Mid June to October is the normal rainy season. Fig. 1: Location Map of Study Area showing Amreli District III. DATA COLLECTION AND DATA GENERATION Data Collection: Satellite (IRS P-6) LISS-III image data and Geo spatial data are obtained from Bhaskaracharya Institute for Space Application and Geo-Informatics, (BISAG), Gandhinagar, Gujarat, India. Hydrological data like precipitation data are collected from state water data center. DEM data has been obtained from USGS site Data Generation: Thematic maps like watershed map, soil map and soil cover complex maps were generated in Arc GIS. IV. METHODOLOGY In the early 1950s, the United States Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) (then named the Soil Conservation Service (SCS) developed a method for estimating runoff from rainfall. This method also referred as the CN method. The SCS curve number method is based on the water balance equation & two fundamental hypotheses which are stated as, 1).ratio of the actual direct runoff to the potential runoff is equal to the ratio of the actual infiltration to the potential infiltration, and 2).the amount of initial abstraction is some fraction of the potential infiltration. (Hand book of Hydrology 1972). Q/(p-Ia)= F/S ……………… (1) F=P(Ia-Q) ……………. (2) Substituting eq. (2) in eq. (1) and by solving; Q=(P-Ia)2/((P-Ia)+3) …………….(3) Where, Q = actual runoff (mm), P = rainfall (mm), Ia = initial abstraction, which represents all the losses before the runoff begins and is given by the empirical equation. Ia=0.2S ……………. (4) Substituting eq. (4) in eq. (3); the eq. (3) becomes Q=(P-0.2S)2/((p+0.8S)) For P>Ia(0.2S)……………………… (5) S = the potential infiltration after the runoff begins given by following equation. S=25400/CN-254………………………….. (6) Where, CN is Curve Number. The CN (dimensionless number ranging from0 to 100) is determined from a table, based on land-cover, HSG, and AMC. HSG is expressed in terms of four groups (A, B, C, D), according to the soil’s infiltration rate. AMC is expressed in three levels (I, II and III), according to rainfall limits for dormant and growing seasons. CN value was adopted from Technical release (TR-55) All rights reserved by www.ijste.org 368 Determination of Surface Runoff in Amreli District Gujarat, India using GIS based SCS Curve Number Method (IJSTE/ Volume 2 / Issue 11 / 066) Although, SCS method is originally designed for use in area of 15 km2, it has been modified for application to larger area by weighing curve numbers with respect to watershed/land cover area. CNw=∑〖 (CNi*Ai) 〗)/A ………………. (7) Where CNw is the weighted curve number; CNi is the curve number from 1 to any number; Ai is the area with curve number CNi; and A the total area of the District V. METHODOLOGY FOR SCS-CN METHOD Fig. 2: Satellite Image of Study Area Fig. 3: Land Use Map Fig. 4: Soil Map All rights reserved by www.ijste.org 369 Determination of Surface Runoff in Amreli District Gujarat, India using GIS based SCS Curve Number Method (IJSTE/ Volume 2 / Issue 11 / 066) Fig. 5: Hydrologic Soil Group Map Table – 1 Runoff Curve Numbers (Amc Ii) For Soil Cover VI. RESULT AND DISCUSSION Surface runoff is estimated using SCS curve number method. Table 2 shows the value of weighted curve number which is 86.58 .Fig.2 shows the graph of rainfall-runoff of 2015 and fig 2 shows the graph of Rainfall-Runoff of 23rd, 24th and 25th june 2015 when highest rainfall occurred in Amreli District Gujarat, India. All rights reserved by www.ijste.org 370 Determination of Surface Runoff in Amreli District Gujarat, India using GIS based SCS Curve Number Method (IJSTE/ Volume 2 / Issue 11 / 066) Table – 2 Calculation of Weighted Curve Number Land Use soil type CN Area in sq.km % of Area % of Area*CN WCN Agriculture B 71 148.681 2.037814263 144.6848127 C 88 5710.594 78.26911241 6887.681893 D 91 126.374 1.73207565 157.6188841 Built Up B 90 4.382 0.06005947 5.405352325 C 94 97.206 1.332300517 125.2362486 D 95 3.1274 0.042863986 4.072078685 Forest B 66 29.295 0.401515788 26.50004199 C 77 419.377 5.747959942 442.5929155 D 83 13.881 0.190252284 15.79093954 Others B 70 0.065 0.000890887 0.06236207 C 74 9.286 0.127273446 9.418235014 86.56 D 78 0.177 0.002425953 0.189224337 wasteland B 67 31.266 0.428530214 28.71152434 C 77 473.83 6.494290005 500.0603304 D 83 12.122 0.166143519 13.78991205 waterbodies B 100 5.223 0.071586174 7.158617372 C 100 153.266 2.100656041 210.0656041 D 100 1.153247 0.015806345 1.580634503 wetlands B 97 1.107 0.015172486 1.471731141 C 97 55.243 0.757157763 73.44430299 D 97 0.446 0.006112853 0.592946783 7296.101647 100 8656.128591 Rainfall –Runoff of 2015 Fig.
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